LangChain Agents (GANLP)
ReAct-style tool loop with bounded steps, structured scratchpad, and traces that show when the agent should defer instead of guessing.
Stack
What was my role?
I was the sole implementer for this coursework module: scoped requirements, wrote the code and experiments for “LangChain Agents (GANLP),” and produced the write-up with metrics and limitations.
Situation
Course lab for “LangChain Agents (GANLP)”: short deadlines, public or synthetic data, and rubrics that reward reproducible notebooks and honest limitations.
Task
Produce a small credible artifact—clean repo or notebook—with baselines, evaluation, and a crisp story of what would change in production.
Action
Implemented end-to-end (ReAct-style tool loop with bounded steps, structured scratchpad, and traces that show when the agent should defer instead of guessing.), logged experiments, compared alternatives, and documented dependencies plus failure cases.
Result
Submitted a runnable deliverable with metrics, repeatable setup commands, and a trade-off section suitable for extending to real systems.